2.5D woven SiO2f/SiO2 composites possess geometric variabilities across scales, such as the spatial fluctuations of fibers and yarns or the random distributions of defects and pores formed in the manufacturing process, which induces a complex stress and strain distribution in material testing. In this study, a multivariate cross-correlated non-Gaussian random field based on Vine Copula is proposed to characterize the spatial variability of mechanical properties. A database of material mechanical properties is acquired by stochastic representative volume element (SRVE) simulation results which contains realistic meso-geometry characteristics and spatially random voids. Based on this database, the cross- and auto-correlations of the mechanical properties are quantified by Vine Copula and non-Gaussian random field model. In a comparison of different numerical models and experimental results, the proposed method is verified, which shows great advantages in characterizing the spatial variability and big potential abilities in damage or reliability analysis.